AIMC Topic: Electronic Health Records

Clear Filters Showing 1 to 10 of 2549 articles

Multimodal Integration in Health Care: Development With Applications in Disease Management.

Journal of medical Internet research
Multimodal data integration has emerged as a transformative approach in the health care sector, systematically combining complementary biological and clinical data sources such as genomics, medical imaging, electronic health records, and wearable dev...

Natural language processing assisted detection of inappropriate proton pump inhibitor use in adult hospitalised patients.

European journal of hospital pharmacy : science and practice
OBJECTIVES: To establish a clinical application monitoring system for proton pump inhibitors (PPI-MS) and to enhance the detection and intervention of inappropriate PPI use in adult hospitalised patients.

Symptom Recognition in Medical Conversations Via multi- Instance Learning and Prompt.

Journal of medical systems
With the widespread adoption of electronic health record (EHR) systems, there is a crucial need for automatic extraction of key symptom information from medical dialogue to support intelligent medical record generation. However, symptom recognition i...

Leveraging BERT for embedding ICD codes from large scale cardiovascular EMR data to understand patient diagnostic patterns.

BMC medical informatics and decision making
The integration of electronic medical records (EMRs) with artificial intelligence (AI) is enhancing medical research, particularly in real-world evidence (RWE) studies. Extracting insights from coded medical data, such as ICD-10 codes, is essential f...

Unveiling social determinants of health impact on adverse pregnancy outcomes through natural language processing.

Scientific reports
Understanding the role of Social Determinants of Health (SDoH) in pregnancy outcomes is critical for improving maternal and infant health yet extracting SDoH from unstructured electronic health records remains challenging. We trained and evaluated na...

Health Care Professionals' Experiences and Opinions About Generative AI and Ambient Scribes in Clinical Documentation: Protocol for a Scoping Review.

JMIR research protocols
BACKGROUND: Generative artificial intelligence (GenAI) leverages large language models (LLMs) that are transforming health care. Specialized ambient GenAI tools, like Nuance Dax, Speke, and Tandem Health, "listen" to consultations and generate clinic...

Comparison of machine learning models for mucopolysaccharidosis early diagnosis using UAE medical records.

Scientific reports
Rare diseases, such as Mucopolysaccharidosis (MPS), present significant challenges to the healthcare system. Some of the most critical challenges are the delay and the lack of accurate disease diagnosis. Early diagnosis of MPS is crucial, as it has t...

Understanding Clinician Perceptions of GenAI: A Mixed Methods Analysis of Clinical Documentation Tasks.

Journal of medical systems
This mixed-methods study evaluated clinicians' user experience (UX) with Generative AI (GenAI) in Electronic Health Record (EHR) systems across three clinical documentation tasks (Information Extraction, Summarization, and Speech-to-Text) at varying ...

Retrospective study of onychomycosis patients treated with ciclopirox 8% HPCH and oral antifungals applying artificial intelligence to electronic health records.

Scientific reports
We conducted a multicenter retrospective analysis of 408 patients diagnosed with onychomycosis who attended three tertiary care Spanish hospitals. The study was conducted to assess the clinical characteristics and outcomes of onychomycosis patients u...

A patient-centered approach to developing and validating a natural language processing model for extracting patient-reported symptoms.

Scientific reports
Patient-reported symptoms provide valuable insights into patient experiences and can enhance healthcare quality; however, effectively capturing them remains challenging. Although natural language processing (NLP) models have been developed to extract...